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Biometrics is a scientific journal emphasizing the role of statistics
and mathematics in the biological sciences. Its object is to promote and extend
the use of mathematical and statistical methods in pure and applied biological
sciences by describing developments in these methods and their applications
in a form readily assimilable by experimental scientists.
JSTOR provides a digital archive of the print version of Biometrics.
The electronic version of Biometrics is available at http://www.blackwell-synergy.com/servlet/useragent?func=showIssues&code=biom.
Authorized users may be able to access the full text articles at this site.

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publisher has elected to have a "zero" moving wall, so their current
issues are available in JSTOR shortly after publication.
Note: In calculating the moving wall, the current year is not counted.
For example, if the current year is 2008 and a journal has a 5 year
moving wall, articles from the year 2002 are available.

Terms Related to the Moving Wall

Fixed walls: Journals with no new volumes being added to the archive.

Absorbed: Journals that are combined with another title.

Complete: Journals that are no longer published or that have been
combined with another title.

Abstract

The Hardy-Weinberg law plays an important role in the field of population genetics and often serves as a basis for genetic inference. Because of its importance, much attention has been devoted to tests of Hardy-Weinberg proportions (HWP) over the decades. It has long been recognized that large-sample goodness-of-fit tests can sometimes lead to spurious results when the sample size and/or some genotypic frequencies are small. Although a complete enumeration algorithm for the exact test has been proposed, it is not of practical use for loci with more than a few alleles due to the amount of computation required. We propose two algorithms to estimate the significance level for a test of HWP. The algorithms are easily applicable to loci with multiple alleles. Both are remarkably simple and computationally fast. Relative efficiency and merits of the two algorithms are compared. Guidelines regarding their usage are given. Numerical examples are given to illustrate the practicality of the algorithms.